Scale across your own GPUs
Schedule and scale model workloads efficiently — on-prem or in your private cloud.
/Why this matters
Idle GPUs and unpredictable bursts
Serving AI at scale on your own hardware means keeping expensive GPUs busy without over-provisioning — and never bursting sensitive workloads to a public cloud. Orchestration handles both.
The cost of borrowed intelligence
/How it works
How it works
Register capacity
Point the orchestrator at the GPU capacity you already own.
Schedule workloads
Uniforge schedules inference and agent workloads across it efficiently.
Scale in place
Scale up or down without ever leaving your environment.
/Capabilities
Orchestration capabilities
/Fits your stack
Runs where your data lives
Databases
PostgreSQL and your operational and analytical data stores.
Automation Tools
n8n, LangChain, Claude Code, and your custom applications.
Design partners
Own the intelligence layer
MiraeAI Uniforge is being built with a small group of design partners in regulated industries. We deploy a governed pilot in weeks, inside your environment, alongside our team.
Become a design partner/FAQ
Questions we hear often
No. Orchestration keeps everything on the capacity you register — there is no burst-to-public-cloud path that could leak data.